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cs.CV2021
A Positive/Unlabeled Approach for the Segmentation of Medical Sequences using Point-Wise Supervision
Laurent Lejeune, Raphael Sznitman
The ability to quickly annotate medical imaging data plays a critical role in training deep learning frameworks for segmentation. Doing so for image volumes or video sequences is e…
cs.CV2018
Iterative multi-path tracking for video and volume segmentation with sparse point supervision
Laurent Lejeune, Jan Grossrieder, Raphael Sznitman
Recent machine learning strategies for segmentation tasks have shown great ability when trained on large pixel-wise annotated image datasets. It remains a major challenge however t…
cs.CV2017
Expected exponential loss for gaze-based video and volume ground truth annotation
Laurent Lejeune, Mario Christoudias, Raphael Sznitman
Many recent machine learning approaches used in medical imaging are highly reliant on large amounts of image and ground truth data. In the context of object segmentation, pixel-wis…